Overview

Dataset statistics

Number of variables8
Number of observations2420
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory153.6 KiB
Average record size in memory65.0 B

Variable types

DateTime1
TimeSeries5
Boolean1
Numeric1

Timeseries statistics

Number of series5
Time series length2420
Starting point2010-01-04 00:00:00
Ending point2019-08-19 00:00:00
Period1 day, 10 hours and 51 minutes
2026-02-01T22:33:20.613362image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.764341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Alerts

repaired? has constant value "False"Constant
adj close is highly overall correlated with close and 3 other fieldsHigh correlation
close is highly overall correlated with adj close and 3 other fieldsHigh correlation
high is highly overall correlated with adj close and 3 other fieldsHigh correlation
low is highly overall correlated with adj close and 3 other fieldsHigh correlation
open is highly overall correlated with adj close and 3 other fieldsHigh correlation
adj close is non stationaryNon stationary
close is non stationaryNon stationary
high is non stationaryNon stationary
low is non stationaryNon stationary
open is non stationaryNon stationary
adj close is seasonalSeasonal
close is seasonalSeasonal
high is seasonalSeasonal
low is seasonalSeasonal
open is seasonalSeasonal
Date has unique valuesUnique
volume has 32 (1.3%) zerosZeros

Reproduction

Analysis started2026-02-02 04:33:17.535862
Analysis finished2026-02-02 04:33:20.540845
Duration3 seconds
Software versionydata-profiling vv4.18.1
Download configurationconfig.json

Variables

Date
Date

Unique 

Distinct2420
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size37.8 KiB
Minimum2010-01-04 00:00:00
Maximum2019-08-19 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-02-01T22:33:21.032189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:21.112760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

adj close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct631
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.3285
Minimum1051
Maximum1889
Zeros0
Zeros (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:21.214921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1051
5-th percentile1117
Q11222
median1289
Q31403.25
95-th percentile1720.05
Maximum1889
Range838
Interquartile range (IQR)181.25

Descriptive statistics

Standard deviation180.13868
Coefficient of variation (CV)0.1342987
Kurtosis0.071151135
Mean1341.3285
Median Absolute Deviation (MAD)79
Skewness0.99405291
Sum3246015
Variance32449.945
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3115491291
2026-02-01T22:33:21.310454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:21.560670image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps502
min3 days
max5 days
mean3 days, 3 hours and 15 minutes
std8 hours, 21 minutes and 36.73 seconds
2026-02-01T22:33:22.338947image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
124419
 
0.8%
128618
 
0.7%
122417
 
0.7%
127217
 
0.7%
126615
 
0.6%
122615
 
0.6%
123415
 
0.6%
132415
 
0.6%
131614
 
0.6%
122914
 
0.6%
Other values (621)2261
93.4%
ValueCountFrequency (%)
10511
 
< 0.1%
10521
 
< 0.1%
10541
 
< 0.1%
10561
 
< 0.1%
10602
0.1%
10622
0.1%
10631
 
< 0.1%
10641
 
< 0.1%
10651
 
< 0.1%
10663
0.1%
ValueCountFrequency (%)
18891
< 0.1%
18741
< 0.1%
18701
< 0.1%
18581
< 0.1%
18561
< 0.1%
18541
< 0.1%
18491
< 0.1%
18281
< 0.1%
18272
0.1%
18261
< 0.1%
2026-02-01T22:33:21.391015image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

close
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct631
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.3285
Minimum1051
Maximum1889
Zeros0
Zeros (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:22.811559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1051
5-th percentile1117
Q11222
median1289
Q31403.25
95-th percentile1720.05
Maximum1889
Range838
Interquartile range (IQR)181.25

Descriptive statistics

Standard deviation180.13868
Coefficient of variation (CV)0.1342987
Kurtosis0.071151135
Mean1341.3285
Median Absolute Deviation (MAD)79
Skewness0.99405291
Sum3246015
Variance32449.945
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3115491291
2026-02-01T22:33:22.908302image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:23.166279image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps502
min3 days
max5 days
mean3 days, 3 hours and 15 minutes
std8 hours, 21 minutes and 36.73 seconds
2026-02-01T22:33:24.022271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
124419
 
0.8%
128618
 
0.7%
122417
 
0.7%
127217
 
0.7%
126615
 
0.6%
122615
 
0.6%
123415
 
0.6%
132415
 
0.6%
131614
 
0.6%
122914
 
0.6%
Other values (621)2261
93.4%
ValueCountFrequency (%)
10511
 
< 0.1%
10521
 
< 0.1%
10541
 
< 0.1%
10561
 
< 0.1%
10602
0.1%
10622
0.1%
10631
 
< 0.1%
10641
 
< 0.1%
10651
 
< 0.1%
10663
0.1%
ValueCountFrequency (%)
18891
< 0.1%
18741
< 0.1%
18701
< 0.1%
18581
< 0.1%
18561
< 0.1%
18541
< 0.1%
18491
< 0.1%
18281
< 0.1%
18272
0.1%
18261
< 0.1%
2026-02-01T22:33:22.992198image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

high
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct641
Distinct (%)26.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1348.1339
Minimum1062
Maximum1912
Zeros0
Zeros (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:24.521769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1062
5-th percentile1124
Q11226
median1293
Q31413
95-th percentile1728
Maximum1912
Range850
Interquartile range (IQR)187

Descriptive statistics

Standard deviation181.90588
Coefficient of variation (CV)0.13493162
Kurtosis0.094607715
Mean1348.1339
Median Absolute Deviation (MAD)78
Skewness1.0053607
Sum3262484
Variance33089.751
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3117663984
2026-02-01T22:33:24.619152image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:24.865566image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps502
min3 days
max5 days
mean3 days, 3 hours and 15 minutes
std8 hours, 21 minutes and 36.73 seconds
2026-02-01T22:33:25.675196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
127415
 
0.6%
128515
 
0.6%
129215
 
0.6%
128815
 
0.6%
129415
 
0.6%
132115
 
0.6%
128714
 
0.6%
122414
 
0.6%
129314
 
0.6%
123414
 
0.6%
Other values (631)2274
94.0%
ValueCountFrequency (%)
10621
 
< 0.1%
10651
 
< 0.1%
10661
 
< 0.1%
10682
0.1%
10703
0.1%
10723
0.1%
10732
0.1%
10741
 
< 0.1%
10752
0.1%
10762
0.1%
ValueCountFrequency (%)
19121
< 0.1%
19091
< 0.1%
18951
< 0.1%
18841
< 0.1%
18811
< 0.1%
18742
0.1%
18701
< 0.1%
18531
< 0.1%
18521
< 0.1%
18431
< 0.1%
2026-02-01T22:33:24.698785image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

low
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct636
Distinct (%)26.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1334.2426
Minimum1045
Maximum1864
Zeros0
Zeros (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:26.157841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1045
5-th percentile1110
Q11216
median1284
Q31391
95-th percentile1709.1
Maximum1864
Range819
Interquartile range (IQR)175

Descriptive statistics

Standard deviation178.29975
Coefficient of variation (CV)0.13363369
Kurtosis0.051879058
Mean1334.2426
Median Absolute Deviation (MAD)78.5
Skewness0.98223784
Sum3228867
Variance31790.802
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3074901113
2026-02-01T22:33:26.250813image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:26.460934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps502
min3 days
max5 days
mean3 days, 3 hours and 15 minutes
std8 hours, 21 minutes and 36.73 seconds
2026-02-01T22:33:27.236623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
127917
 
0.7%
122216
 
0.7%
119616
 
0.7%
132616
 
0.7%
128215
 
0.6%
132815
 
0.6%
131215
 
0.6%
127415
 
0.6%
128414
 
0.6%
132014
 
0.6%
Other values (626)2267
93.7%
ValueCountFrequency (%)
10451
< 0.1%
10461
< 0.1%
10502
0.1%
10511
< 0.1%
10521
< 0.1%
10531
< 0.1%
10581
< 0.1%
10592
0.1%
10602
0.1%
10622
0.1%
ValueCountFrequency (%)
18641
< 0.1%
18581
< 0.1%
18351
< 0.1%
18301
< 0.1%
18291
< 0.1%
18251
< 0.1%
18241
< 0.1%
18141
< 0.1%
18111
< 0.1%
18091
< 0.1%
2026-02-01T22:33:26.324668image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

open
Numeric time series

High correlation  Non stationary  Seasonal 

Distinct640
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.5438
Minimum1052
Maximum1909
Zeros0
Zeros (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:27.720483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1052
5-th percentile1118
Q11222.75
median1289
Q31404.25
95-th percentile1722
Maximum1909
Range857
Interquartile range (IQR)181.5

Descriptive statistics

Standard deviation180.38004
Coefficient of variation (CV)0.13445707
Kurtosis0.077134685
Mean1341.5438
Median Absolute Deviation (MAD)78.5
Skewness0.99706676
Sum3246536
Variance32536.96
MonotonicityNot monotonic
Augmented Dickey-Fuller test p-value0.3203984066
2026-02-01T22:33:27.816084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
2026-02-01T22:33:28.152960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Gap statistics

number of gaps502
min3 days
max5 days
mean3 days, 3 hours and 15 minutes
std8 hours, 21 minutes and 36.73 seconds
2026-02-01T22:33:29.070213image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
129220
 
0.8%
128519
 
0.8%
125618
 
0.7%
124816
 
0.7%
121215
 
0.6%
127415
 
0.6%
119814
 
0.6%
131214
 
0.6%
122714
 
0.6%
127914
 
0.6%
Other values (630)2261
93.4%
ValueCountFrequency (%)
10521
 
< 0.1%
10542
0.1%
10561
 
< 0.1%
10621
 
< 0.1%
10632
0.1%
10641
 
< 0.1%
10653
0.1%
10661
 
< 0.1%
10681
 
< 0.1%
10692
0.1%
ValueCountFrequency (%)
19091
< 0.1%
18861
< 0.1%
18692
0.1%
18581
< 0.1%
18521
< 0.1%
18431
< 0.1%
18391
< 0.1%
18331
< 0.1%
18311
< 0.1%
18291
< 0.1%
2026-02-01T22:33:27.891644image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ACF and PACF

repaired?
Boolean

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size21.3 KiB
False
2420 
ValueCountFrequency (%)
False2420
100.0%
2026-02-01T22:33:29.482993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

volume
Real number (ℝ)

Zeros 

Distinct901
Distinct (%)37.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5835.1264
Minimum0
Maximum386334
Zeros32
Zeros (%)1.3%
Negative0
Negative (%)0.0%
Memory size37.8 KiB
2026-02-01T22:33:29.536027image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q135
median124
Q3424.25
95-th percentile6997.45
Maximum386334
Range386334
Interquartile range (IQR)389.25

Descriptive statistics

Standard deviation30618.806
Coefficient of variation (CV)5.2473251
Kurtosis48.424382
Mean5835.1264
Median Absolute Deviation (MAD)109
Skewness6.6859213
Sum14121006
Variance9.3751126 × 108
MonotonicityNot monotonic
2026-02-01T22:33:29.616460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
032
 
1.3%
2025
 
1.0%
1424
 
1.0%
723
 
1.0%
423
 
1.0%
823
 
1.0%
523
 
1.0%
2722
 
0.9%
222
 
0.9%
121
 
0.9%
Other values (891)2182
90.2%
ValueCountFrequency (%)
032
1.3%
121
0.9%
222
0.9%
318
0.7%
423
1.0%
523
1.0%
617
0.7%
723
1.0%
823
1.0%
917
0.7%
ValueCountFrequency (%)
3863341
< 0.1%
2908891
< 0.1%
2805461
< 0.1%
2761361
< 0.1%
2754421
< 0.1%
2714571
< 0.1%
2590501
< 0.1%
2544281
< 0.1%
2471681
< 0.1%
2374971
< 0.1%

Interactions

2026-02-01T22:33:20.037163image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.359789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.691881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.029540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.354959image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.705099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.103529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.413618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.744253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.085497image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.407922image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.760776image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.167327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.468414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.809998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.137851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.458673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.813095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.228352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.521247image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.863568image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.189189image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.521225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.866762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.291984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.575917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.914821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.240320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.589391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.919332image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:20.354306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.627337image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:18.965993image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.294007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.641195image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-02-01T22:33:19.970905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-02-01T22:33:29.675603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
adj closeclosehighlowopenvolume
adj close1.0001.0000.9980.9980.9960.013
close1.0001.0000.9980.9980.9960.013
high0.9980.9981.0000.9960.9980.025
low0.9980.9980.9961.0000.998-0.001
open0.9960.9960.9980.9981.0000.013
volume0.0130.0130.025-0.0010.0131.000

Missing values

2026-02-01T22:33:20.451657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-02-01T22:33:20.507409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Dateadj closeclosehighlowopenrepaired?volume
2010-01-042010-01-0411181118112210971118False184
2010-01-052010-01-0511181118112611151118False53
2010-01-062010-01-0611361136113911211136False363
2010-01-072010-01-0711331133113311291133False56
2010-01-082010-01-0811381138113811231138False54
2010-01-112010-01-1111511151116111431151False177
2010-01-122010-01-1211291129115711271129False51
2010-01-132010-01-1311361136113611211136False58
2010-01-142010-01-1411431143114611331137False81
2010-01-152010-01-1511301130113311271133False50
Dateadj closeclosehighlowopenrepaired?volume
2019-08-062019-08-0614721472147514581470False460
2019-08-072019-08-0715071507151014731474False824
2019-08-082019-08-0814981498150814921498False367
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